Previous approaches for instance segmentation submitted to the 2019 ROBUST-MIS challenge, were exclusively based on two-stage detectors such as Mask R-CNN [1]}. While these models exhibited good performances in terms of robustness, they all suffered from very high inference times averaging around 5 fps, preventing them from achieving real-time performances. Realistically, real-time performance is mandatory in order to fully exploit the capabilities of tracking applications in live surgeries.
